SAMAGRA VEDIKA --TELANGANA’S INTEGRATED PLATFORM

Using Big data, ML, Graph data base

FOR BETTER CITIZEN SERVICE DELIVERY AND TRANSPARENCY, ACCOUNTABLE AND EFFICIENT GOVERNANCE

I TE&C DEPARTMENT G OVERNMENT OF TELANG ANA

Student scholarships

Few of the welfare schemes of Telangana Total budget is more than 35,000 Cr

Ration Cards

AasaraPensions

Most of the welfare schemes have eligibility in terms of Income

Raithu Bandhu

Identity Fraud

Quantity Fraud

Eligibility Fraud

These leakages have been controlled

through use of Aadhar & ePOS

Right Beneficiary

Limited means to establish

identify of right beneficiaries.

Research on mitigation is currently

ongoing

No solution in the country as on date

as it requires data of other

departments

Bogus Beneficiary

Non-existent real beneficiary

Duplicate Beneficiary

Multiple registrations by same beneficiary.

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2

3

Illegitimate Claims Claiming bills

in MNREGA without work

Disproportionate Quantity

Availing more quantity of PDS

Food grains than eligibility

Is the person truly eligible? Limited

means to correctly establish the

eligibility

possible leakages in welfare programs and some still unplugged.

Resolution throughTypes of Fraud Leakage on account of

This is probably as big

as a budget of a minor

department!

Quantum Of Leakages Due To Wrong Inclusion

Total Budget For

2019-20 For

Pensions

₹ 10,000 Cr

Value of just 1% Leakage…

₹ 100 Crores

Eligibility for many benefits is prescribed.

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People fulfilling one or more of the following conditions listed below shall not be eligible for

Aasara Pension:

Classification Aspect

Self-Economic

Indicators

Having land more than 3.0 acres wet/ irrigated dry or 7 5 acres dry.

Having large business Enterprise (oil/rice mills, pumps, shop owners etc.).

Owners of light and/or heavy automobiles (four wheelers and big vehicles)

Family Based

Parameters

Having children who are Government/Public sector/ Private sector

employment / Out-sourced/Contract.

Having children who are Doctors, Contractors, Professionals and Self

employed.

Government

PensionerAlready receiving Government pensions or freedom fighter pensions.

Others

Any other criterion in which the verification officer may asses by the

manner of lifestyle, occupation and possession of assets rendering the

household as ineligible

Traditional process → ineffective implementation

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Manual Process

No Digital Trail

High Human Discretion

Reliance on

Aadhar alone Almost no accountability of

officials in either error

Inclusion Error

( Benefit given to

ineligible persons)

Exclusion errors

(Denying eligible

persons)

Effects of ignoring these challenges

Opportunity & Challenges to get Consolidated view

1. Data is in Silos

2. No Common ID

3. Integrated view – (SSOT) Single Source of Truth is not

available

1. Most of the Data is in electronic form

Samagra Vedika One View - Objectives

What is the alternative approach Without using Aadhar or any other ID

But getting the same efficacy In view of Legal restrictions on use of Aadhar

Meta data attributes of an entity present in all data sources

• Following meta data information is available in every data source

Unique Personal Details

– Name

– DOB

– Fathers Name ( In Some)

Unique ID* Number

– PAN or

– Passport no or

– Voter ID or

– Driving LicenseContact Details

– Mobile No. ( In some)

– Address (Res)

– Address (Off)

Photograph (

Some data sets) *Any one ID is present

• All records in all data sources have Name, Address.

• Some records also have DoB, Phone Number, Fathers Name, Photo

• Can a combination of these attributes which are already available in every record be used to identify an entity

• With an Accuracy nearer to Aadhar based linkage

• With no manual intervention

3 “V” CHALLENGES

Examples of variations in Name & Father’s Name

Spelling

Abbreviations

Sequence Variation

Addition/ Deletion

Splitting

• N Radha Murali Krishna

• N Radha Muralee Krishna

• N R Murali Krishna

• N R M Krishna

• Murali Krishna N Radha

• N M Radha Krishna

• N Murali Krishna

• Murali Krishna

• Murali Krishna N Radha

• Radhakrishna N M

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Key Performance Metrics

FOLLOWING TECHNOLOGIES ARE USED

Economic Survey 2019 of GOI has praised Samagra Vedika

Accurate targeting of subsidies

Beneficiaries for Old age pensions

Using Samagra Vedika for new sanctions of Aasara Pensions

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Total new applications

received

Total eligible applications

(as per Samagra Vedika)

Total ineligible applications

(as per Samagra Vedika)

65,693 59,068

6,625 (10.1%)

Value Rs 16 Cr per anum

Eligibility for Aasara Pensions is now 57 years

New applications are being received (expected about 7 to 8 lakh new pensioners )

65,693 new applications approved by the Districts officials after verification

Are sent to SERP for sanction Aasara Pensions

In Aug 2019 SERP requested ITEC to check the eligibility

Through Samagra Vedika platform

Accurate targeting of subsidies

Predictive analytics based identification of beneficiaries for 2 BHK scheme using Big data

Govt of Telangana has a program to provide 2BHK houses to

economically weaker sections

• Started in 2015 by the Govt. Of Telangana to provide 100% subsidized housing to the poor.

• No beneficiary contribution needed – one of its kind in India.

• Construction cost = 7-8 lakhs/house and total cost including land is 15-20 lakhs/house

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Total Houses constructed

under the scheme

Total applications received

2000

11,681

In one district

Aligned with the objective of implementation of scheme in the entire state, Govt of Telangana is looking to distribute 2BHK houses to

eligible persons.

The significant expenditure by Govt, and high mismatch in number of applicants and available houses has necessitated a very

careful approach towards allotting the houses to applicants.

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Key observations

Earlier Beneficiaries

of Housing Schemes

Already owing

HousesFinancially well-off

applicants

It is difficult to correctly identify the right

beneficiaries

• basis the information collected in the

application form.

• basis any other information available with

district adminstration

• Manual system

Some of the applicants have received

subsidized housing earlier, but are

reapplying using a family members name or

their name

Certain applicants have submitted low

incomes certificates even though they

are financially well offSome applicants or their family

members already own a house.

Siddipet Dist. Administration had following key observations.

Predictive analytics using big data used following data sets available

with Govt.

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❑ Name

❑ Fathers name

❑ Address

❑ Aadhar number

❑ Phone number

❑ Photo of the applicant

❑ Minor info.

Electricity connection

Water connection

House and land database

Old age pension schemes

Vehicles database

Ration card database

datasets available Information provided by applicant

Information about family members not provided

in the application

Common databases are matched with the provided info. and they are further analyzed to bring out valuable insights in

the form of applicant categories

The analysis using Samagra Vedika categorized the applicants in four

categories as follows:

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Categories -> Category 1 Category 2 Category 3 Category 4

Classification Qualify Qualify with verification Consider as low priority Don’t consider

Not financially well off

No housing benefits previously

accepted

No other welfare schemes prior

From Siddipet - SKS

Count (% of Total) 2363 (20.2%) 2678 (22.9%) 2181 (18.7%) 4459 (38.2%)

Pilot at Hyderabad in Aug 2016

In Hyderabad about 1,00,000 cards were removed in Aug 2016

There was some public resistance due to which people were asked to apply again. About 19,000applied as on Dec 16, 14,000 cards were activated again after verification that the property is verysmall or the four wheeler is taken out of loan etc.

Net about 86,000 cards are removed from August 16.

Total subsidy saved is Rs 4.6 Cr every month from Aug 16 onwards.

The mistake of tagging the vehicle/house to a wrong person is less than 5% which shows the efficiency of the application

THANK YOU